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 Automated Machine Learning: How do teams work together on an AutoML project?
In this use case, available to the public on GitHub, we’ll see how a data scientist, project manager, and business lead at a retail grocer can leverage automated machine learning and Azure Machine Learning service to reduce product overstock.
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Fighting Overfitting in Deep Learning
This post outlines an attack plan for fighting overfitting in neural networks.
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The Most In Demand Tech Skills for Data Scientists
By the end of this article you’ll know which technologies are becoming more popular with employers and which are becoming less popular.
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5 Ways to Apply Ethics to AI
Here are six more lessons based on real life examples that I think we should all remember as people working in machine learning, whether you’re a researcher, engineer, or a decision-maker.
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Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released
Ontotext Platform 3.0 features significant technology improvements to enable simpler and faster graph navigation, including GraphQL interfaces to make it easier for application developers to access knowledge graphs without tedious development of back-end APIs or complex SPARQL.
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Automatic Text Summarization in a Nutshell
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about Automatic Text Summarization and the various ways it is used.
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The ravages of concept drift in stream learning applications and how to deal with it
Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios. These streams of data evolve generally over time and may be occasionally affected by a change (concept drift). How to handle this change by using detection and adaptation mechanisms is crucial in many real-world systems.
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Python Dictionary Guide: 10 Python Dictionary Methods & Examples
Master Python Dictionaries and their essential functions in 15 minutes with this introductory guide.
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Deploying a pretrained GPT-2 model on AWS
This post attempts to summarize my recent detour into NLP, describing how I exposed a Huggingface pre-trained Language Model (LM) on an AWS-based web application.
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Deployment of Machine learning models using Flask
This blog will explain the basics of deploying a machine learning algorithm, focusing on developing a Naïve Bayes model for spam message identification, and using Flask to create an API for that model.
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Automated Machine Learning: How do teams work together on an AutoML project?